A Study on Monitoring System for Grinding Wheel Status Based on Acoustic Emission Technology

2011 ◽  
Vol 52-54 ◽  
pp. 2051-2055
Author(s):  
Pei Jiang Li ◽  
Ting You
Keyword(s):  
Acoustic Emission ◽  
High Speed ◽  
Grinding Wheel ◽  
Signal Acquisition ◽  
Wheel Wear ◽  
Processing Efficiency ◽  
Emission Signal ◽  
Grinding Wheel Wear ◽  
Upper Computer

The grinding wheel wear status is an important guarantee for the processing efficiency and processing quality of precision and super precision grinding. In this paper, a USB acoustic emission signal acquisition system is designed for online monitoring of grinding wheel status. In the system, CPLD is used as the controller, and a high-speed A/D converter is used to implement the synchronous acquisition of acoustic emission array signals. The collected data are sent into FIFO, and CY7C68013A is used for USB data transmission with upper computer. The sampling frequency of the system can be 10 MHz, and USB transmission speed can reach 40M/S. It is proved that it can meet the monitoring requirements of grinding wheel wear status well by the grinding processing.

Wear Monitoring on Microcrystalline Aluminum Oxide Grinding Wheels on Profile Grinding with the Aid of Acoustic Emission

2014 ◽  
Vol 894 ◽  
pp. 95-103 ◽  
Author(s):  
Lucas Benini ◽  
Walter Lindolfo Weingaertner ◽  
Lucas da Silva Maciel
Keyword(s):  
Acoustic Emission ◽  
Wear Behavior ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Profile Grinding ◽  
Grinding Wheel Wear ◽  
Abrasive Grains ◽  
Profile Deviation ◽  
Synthetic Materials ◽  
External Cylindrical Grinding

The localized wear on grinding wheel edges is a common phenomenon on profile grinding since the abrasive grains are less attached to the bond. The grinding wheel wear depends heavily on the process parameters, workpiece and wheel composition, causing changes on the process and profile deviation behaviors. In order to cope with these uncertainties, many natural and synthetic materials have been used in different grinding processes. However, the influence of mixed compositions of different types of abrasive grains on external cylindrical grinding is not well known. In order to assess this relation, a methodology procedure was developed providing an overview of the cinematic edges behavior on a progressive wheel wear. The methodology procedure is based on the acoustic emission technology, using a transducer with a 50 μm radius diamond tip. The tip, when in contact with a rotating grinding wheel, enables the evaluation of the cinematic cutting edges. The abrasive grain density was evaluated for different grinding wheel compositions and specific wear removal values. Furthermore, these results were compared to the profile deviation observed on the same tool, allowing the assessment of the influence of different microcrystalline corundum grains on the overall grinding wheel wear behavior.

Based on Multi-Sensor Tool Steel Hard Turning Process Monitoring and Controlling

2010 ◽  
Vol 108-111 ◽  
pp. 549-555 ◽  
Author(s):  
Fei Wu ◽  
Xi Wang ◽  
Wei Wu Zhong ◽  
Hui Yu ◽  
Li Bing Liu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Virtual Instrument ◽  
Hard Turning ◽  
Wavelet Packet ◽  
Signal Acquisition ◽  
Turning Process ◽  
Cooling Fluid ◽  
Emission Signal ◽  
Temperature Signal

Through a set of electro-hydraulic digital valve as the core of the fuzzy control system to provide an appropriate amount of cooling fluid, the hard turning process temperature can be controlled at any set temperature. The use of the signal acquisition system based on virtual instrument, acquisition acoustic emission signals, vibration signals and temperature signals during the hard turning process. The temperature signal is processed by wavelet transform ,after vibration and acoustic emission signals be processed by wavelet packet decomposition and energy method, it is found that through providing appropriate cooling fluid can control temperatures in the processing and decrease the amplitude of vibration and acoustic emission signal, it also means that we can improve the quality of processing, and prolong the life of tool.

Experimental evaluation on grinding wheel wear through vibration and acoustic emission

Wear ◽  
1998 ◽  
Vol 217 (1) ◽  
pp. 7-14 ◽  
Author(s):  
A. Hassui ◽  
A.E. Diniz ◽  
J.F.G. Oliveira ◽  
J. Felipe ◽  
J.J.F. Gomes
Keyword(s):  
Acoustic Emission ◽  
Experimental Evaluation ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear

An Investigation of Grinding and Wheel Loading Using Acoustic Emission

1984 ◽  
Vol 106 (1) ◽  
pp. 28-33 ◽  
Author(s):  
D. Dornfeld ◽  
He Gao Cai
Keyword(s):  
Acoustic Emission ◽  
Chip Thickness ◽  
Process Efficiency ◽  
Grinding Wheel ◽  
Force Measurements ◽  
Wheel Wear ◽  
Emission Signal ◽  
Wheel Loading ◽  
Loss Of Contact ◽  
Higher Sensitivity

This paper investigates the potential for using acoustic emission signal analysis for a monitoring technique for process automation as well as a sensitive tool for investigation of grinding fundamentals. The acoustic emission generated during the grinding process is analyzed to determine its sensitivity to process efficiency and the condition of the grinding wheel. Acoustic emission from surface grinding is used to measure wear-related loading of the grinding wheel and sparkout (or loss of contact) between the wheel and the work surface. A discussion of energy dissipation in grinding and the generation of acoustic emission is included. This investigation showed that the acoustic emission energy, (RMS)2, increases with the combined effects of wheel wear and loading, the signal energy, (RMS)2, is a function of the undeformed chip thickness and that the signal accurately detects work-wheel contact and sparkout with a higher sensitivity than force measurements.

In-process Identification of System Time Constant for the Adaptive Control of Grinding

1995 ◽  
Vol 117 (2) ◽  
pp. 194-201 ◽  
Author(s):  
D. A. Thomas ◽  
D. R. Allanson ◽  
J. L. Moruzzi ◽  
W. Brian Rowe
Keyword(s):  
Time Constant ◽  
Dwell Time ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear ◽  
Grinding Conditions ◽  
Axis Position ◽  
Grinding Power ◽  
System Time

The forces generated during the grinding process cause deflections of the machine-grinding wheel-workpiece system which are large compared to the accuracies required. The deflections cannot be precisely predicted and the optimum grinding conditions vary because the grinding wheel sharpness changes with grinding wheel wear and dressing. In practice conservative machining conditions and feed cycles are used in order to maintain the quality of the finished workpieces. This paper presents a new method of characterizing the time constant of the system from the grinding power consumption during the infeed section of a grinding cycle. Adaptive grinding cycles have been implemented which use the measured value of system time constant to control the target axis position and the dwell time. In this way the control system adapts the machining cycle for the wheel condition at the time of grinding, and can cope with the large variations in deflection that occur when using high feedrates.

An Intelligent Grinding Wheel Wear Monitoring System Based on Acoustic Emission

2017 ◽  
Vol 261 ◽  
pp. 195-200 ◽  
Author(s):  
Ning Ding ◽  
Chang Long Zhao ◽  
Xi Chun Luo ◽  
Jian Shi
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Monitoring System ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear ◽  
Wear Monitoring ◽  
Grinding Machine ◽  
Ae Signals ◽  
Wear Condition

Acoustic emission (AE) signals can provide tool condition that is critical to effective process control. However, how to process the data and extract useful information are challenging tasks. This paper presented an intelligent grinding wheel wear monitoring system which was embedded in a surface grinding machine. An AE sensor was used to collect the grinding signals. The grinding wheel wear condition features were extracted by a proposed novel method based on statistics analysis of the average wavelet decomposition coefficient. The detailed signal characteristics during different wear condition are described. A BP neural network was used to classify the conditions of the grinding wheel wear. The inputs of the neural network were the three extracted features, and the outputs were three different states of grinding wheel condition, namely primary wear, intermediate wear and serious wear. The intelligent monitoring system was evaluated through grinding experiments. The results indicate that the effectiveness of the proposed method for extracting features of AE signals and developed intelligent grinding wheel wear monitoring system are satisfied.

Design and Implementation of Valve Failure Signal Multi-Channel Acquisition System Based on Acoustic Emission and Pipeline

2012 ◽  
Vol 460 ◽  
pp. 281-285
Author(s):  
Ting Feng ◽  
Jian De Wu ◽  
Xu Yi Yuan ◽  
Yu Gang Fan ◽  
Xiao Dong Wang
Keyword(s):  
Acoustic Emission ◽  
High Speed ◽  
Gain Control ◽  
Control Unit ◽  
High Sensitivity ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Emission Data ◽  
Emission Signal ◽  
Data Output

Designed and implemented acoustic emission signal acquisition system core with microprocessor STM32F103RB. Acquisition system included high sensitivity acoustic emission sensors: PXR20; signal conditioning for acoustic emission, used high-speed ADC AD9225 for A/D conversion; used FIFO module for data buffer; used USB to serial port technology for data communications and transmissions. Central control unit design included gain control of amplifier circuit, clock control of external AD-chip and data cache chip, data acquisition port control, data output port control. Experimental results show that the system implements a multi-channel, parallel, high-precision acquisition and transmission for acoustic emission data.

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